CN104919252A - Room temperature estimating device, program - Google Patents
Room temperature estimating device, program Download PDFInfo
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- CN104919252A CN104919252A CN201480004442.1A CN201480004442A CN104919252A CN 104919252 A CN104919252 A CN 104919252A CN 201480004442 A CN201480004442 A CN 201480004442A CN 104919252 A CN104919252 A CN 104919252A
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- room temperature
- outside air
- air temperature
- predictor formula
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/89—Arrangement or mounting of control or safety devices
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/10—Temperature
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/10—Temperature
- F24F2110/12—Temperature of the outside air
Abstract
This room temperature estimating device (10) is provided with a storage unit (13), a predictive expression generating unit (15), a predicted shift acquisition unit (16) and a room temperature estimating unit (17). The predictive expression generating unit (15) uses data which is stored in the storage unit (13) and which relates to the outside temperature and room temperature at a specific time on multiple days in a prescribed extraction period to generate a predictive expression which represents the relation between the room temperature and the outside temperature for said specific time. The room temperature estimating unit (17) uses the shifts in the outside temperature acquired by the predicted shift acquisition unit (16) to calculate the outside temperature for a day and time of interest corresponding to the aforementioned specific time, and estimates the room temperature of said day and time of interest by substituting the outside temperature into the predictive expression.
Description
Technical field
The present invention relates to the room temperature estimation unit of the room temperature being configured to the date and time that estimation is paid close attention to and make computer be used as the program of this room temperature estimation unit.
Background technology
Traditionally, there will be a known and at predetermined instant, room temperature is adjusted to the technology of preferred temperature (such as the information relevant with the outside air temperature predicted based on the time variations with room temperature, see Japanese Patent Patent, flat 6-42765 is disclosed, hereinafter referred to as " document 1 ").In addition, about the temperature in vehicle, also there will be a known following technology, wherein this technology is used for the change predicting the temperature of interior space based on the change of estimated sunshine amount, measured outside air temperature and measured interior space temperature, and give a warning (such as when predicting interior space temperature and reaching predetermined threshold, see the open 2005-343386 of Japanese Patent Patent, hereinafter referred to as " document 2 ").
Document 1 discloses the technology predicting the time variations of room temperature for measuring room temperature as environmental information and based on the history of measured room temperature.The heating capacity that document 1 also discloses for heating required heat (hereinafter referred to as " heating load energy ") and heating combined equipment based on the time variations of predicted room temperature and outside air temperature, room is determined the operation start time of heating combined equipment and heats the technology of start time.Particularly, in document 1, determine the predicted value of room temperature and outside air temperature, and calculate the heating load energy for room temperature being adjusted to preferred temperature based on these predicted values.
In the structure described in document 1, prediction room temperature is to calculate heating load energy.But in document 1, the historical data based on room temperature predicts room temperature.Document 1 the unexposed other factors for using room temperature to rely on are to predict the technology of room temperature.
Document 2 discloses following technology, and wherein this technology is used for the gentle outside air temperature of measuring chamber as environmental information, and estimates interior space temperature based on measured room temperature and measured outside air temperature and the sunshine amount predicted.
Structure described in document 2 relates to prediction interior space temperature.It should be noted that interior space temperature follows outside air temperature at short notice when outside air temperature changes.Therefore, relatively easily interior space temperature is predicted based on outside air temperature and sunshine amount.On the other hand, the thermal characteristics of the such as heat-insulating property of the temperature-independent in rooms of buildings in room etc., and do not change immediately when outside air temperature changes.Therefore, based on the technology described in document 2, be difficult to the room temperature come according to outside air temperature in predict good room.
Also there will be a known for the various factors of the presence or absence based on the heat-insulating property of such as outside air temperature, building, sunshine, ventilation, rainfall and people etc., the technology by using computer simulation to carry out the room temperature of predict good.But this computer simulation needs bulk information, and special measurement may be needed to obtain right value.Therefore, this technology is not easy to the prediction carrying out room temperature.
Summary of the invention
The object of this invention is to provide for estimating the room temperature estimation unit of the temperature in the room in building and the program for making computer be used as this room temperature estimation unit based on measured environmental information when the computer simulation without the need to complexity.
According to a kind of room temperature estimation unit of the present invention, comprising: room temperature obtaining portion, it is configured to obtain room temperature data; Outside air temperature obtaining portion, it is configured to obtain outside air temperature data; Storage part, it is configured to the outside air temperature data that the room temperature data that described room temperature obtaining portion obtained and described outside air temperature obtaining portion obtain and stores in the mode be associated with measured date and time respectively; Predictor formula generating unit, it is configured to, based on the appointment moment respective with many days in predetermined extraction time section stored in described storage part corresponding room temperature data and outside air temperature data, generate the predictor formula of the relation between room temperature data and outside air temperature data representing the described appointment moment; Predicted time change obtaining portion, it is configured to the predicted time change obtaining outside air temperature; And room temperature estimator, it is configured to the time variations of the outside air temperature obtained based on described predicted time change obtaining portion, be applied to described predictor formula by with the outside air temperature in described concern moment of specifying the moment corresponding, estimate the room temperature in described concern moment thus.
In this room temperature estimation unit, preferably, described predictor formula generating unit be configured to generate specify the moment and second to specify the moment corresponding respectively with at least the first at least the first predictor formula and the second predictor formula as described predictor formula, wherein said first predictor formula generates based on the described first room temperature data of specifying the moment corresponding respective with many days in described extraction time section and outside air temperature data, and described second predictor formula generates based on the described second room temperature data of specifying the moment corresponding respective with many days in described extraction time section and outside air temperature data, and described room temperature estimator is configured to carry out following operation: be applied to described first predictor formula by with the described first first outside air temperature paying close attention to the moment of specifying the moment corresponding, estimate the room temperature in described first concern moment thus, and be applied to described second predictor formula by with the described second second outside air temperature paying close attention to the moment of specifying the moment corresponding, estimate the room temperature in described second concern moment thus.
In this room temperature estimation unit, preferably, described predictor formula generating unit is configured to generate recurrence formula as described predictor formula according to room temperature data and outside air temperature data.
In this room temperature estimation unit, preferably, described predictor formula generating unit is configured to comprise room temperature data and generate described predictor formula by comprising outside air temperature data as independent variable as the simple linear recursive analysis of dependent variable.
In this room temperature estimation unit, preferably, described extraction time, section was for determined within 1 year, carrying out multi-split obtained each sliced time section based on climatic environment, and described room temperature estimator is configured to based on for the room temperature data in predetermined section sliced time section of determined described extraction time and outside air temperature data and the predictor formula generated is applied to the prediction of the room temperature in this of section predetermined sliced time.
In this room temperature estimation unit, preferably, this room temperature estimation unit also comprises control information obtaining portion, described control information obtaining portion be configured to obtain beyond outside air temperature affect room temperature with from the corresponding control information of a state selected in multiple state, wherein, the state that described predictor formula generating unit is configured to the control information obtained according to described control information obtaining portion corrects described predictor formula, generate thus and correct predictor formula, and described room temperature estimator is configured to estimate room temperature based on described correction predictor formula.
In this room temperature estimation unit, preferably, this room temperature estimation unit also comprises notice efferent, and described notice efferent is configured to export room temperature estimated for described room temperature estimator to notifying device.
In this room temperature estimation unit, preferably, described outside air temperature obtaining portion is configured to obtain the outside air temperature data provided via electrical communication line.
According to a kind of program of the present invention, it is configured to computer is used as according to above-mentioned any room temperature estimation unit.
Utilize structure of the present invention, when the computer simulation without the need to complexity, the temperature in the room in building can be estimated based on the information that can easily measure.
Accompanying drawing explanation
Fig. 1 is the block diagram that embodiment 1 is shown.
Fig. 2 is the figure of the principle for illustration of embodiment 1.
Fig. 3 is the figure of the principle for illustration of embodiment 1.
Fig. 4 is the block diagram that embodiment 2 is shown.
Fig. 5 A and 5B is the figure of the principle for illustration of embodiment 2.
Fig. 6 is the block diagram that embodiment 3 is shown.
Detailed description of the invention
Below explanation is used for the technology using the time variations of predicted outside air temperature to estimate the temperature of not carrying out the room freezing and heat.Under the state of not carrying out freezing and heating, the factor that room temperature relies on comprises the number etc. in outside air temperature, the heat-insulating property in room, sunshine (presence or absence at sunshine and sunshine amount), ventilation (presence or absence of ventilation and ventilation volume), rainfall (presence or absence of rainfall and rainfall) and room.
The heat-insulating property in room is the distinctive characteristic of house, and can estimate the heat-insulating property in room roughly based on the construction method etc. of the construction material of house and house.But, be not easy the heat-insulating property determining room quantitatively.In addition, although can count the number in room, but because the influence degree risen to room temperature is different according to the metabolic rate of these people and the amount of wearing the clothes etc. between each one, be therefore difficult to determine the relation between the number in room temperature and room theoretically.In addition, sunshine, ventilation and rainfall can also be monitored, but be not easy to determine the impact of these factors on room temperature theoretically.
That is, the factor that room temperature relies on can be measured, but be not easy to create the suitable model that these factors and room temperature are linked together.Therefore, be not easy to obtain room temperature according to the measured value of these factors by computer simulation.In addition, input bulk information and correction process can be needed with the computer simulation of the Accuracy extimate room temperature needed for reality.Therefore, estimate that room temperature needs the extensive work of professional person for each room.
Below illustrating can when without the need to coming based on the information that can easily measure with the room temperature estimation unit of the Accuracy extimate room temperature be applicable to when computer simulation based on complex model.In embodiment 1, the technology being used for only estimating room temperature based on outside air temperature is described.In example 2, the next technology estimating room temperature based on outside air temperature of heat-insulating property for considering room is described.In embodiment 3, illustrate for consider sunshine, ventilation, rainfall and indoor the impact of number to estimate the technology of room temperature.
embodiment 1
The room temperature estimation unit 10 of the present embodiment is configured to the predictor formula based on outside air temperature and room temperature being associated, and estimates the room temperature of paid close attention to date and time according to outside air temperature.Therefore, room temperature estimation unit 10 comprises the structure being configured to generation forecast formula and the structure being configured to estimate according to outside air temperature based on this predictor formula room temperature.
Room temperature estimation unit 10 comprises comprising and is configured to performing a programme using the device and interface that realize the processor of the function of the following stated device used as major hardware components.The device comprising processor can be have the microcomputer of internal memory or be provided with the processor etc. of external memory storage.In addition, performing a programme can be used as room temperature estimation unit 10 with the computer realizing the function of the following stated.The program of these kinds can be provided via computer-readable recording medium or be provided by communication via electrical communication line.
First the structure being configured to generation forecast formula in room temperature estimation unit 10 is described.In order to generation forecast formula, need both measurements when making room temperature and outside air temperature is associated with date and time respectively.Therefore, as shown in Figure 1, room temperature estimation unit 10 comprises: room temperature obtaining portion 11, and it is configured to obtain room temperature data (measured value) from indoor temperature measurement portion 21; And outside air temperature obtaining portion 12, it is configured to obtain outside air temperature data (measured value) from outside air temperature measurement section 22.Room temperature estimation unit 10 also comprises storage part 13, timing unit 14 and predictor formula generating unit 15.Storage part 13 is configured to room temperature data (measured value) and outside air temperature data (measured value) to store in the mode be associated with measured date and time respectively.Timing unit 14 is configured to measure current date and time.Predictor formula generating unit 15 is configured to generate the multiple predictor formulas corresponding respectively with the multiple moment in one day.
Indoor temperature measurement portion 21 is arranged on the inside in the room of building, and is configured to measure the temperature (that is, measuring room temperature) in the place being provided with indoor temperature measurement portion 21.Outside air temperature measurement section 22 is arranged on the outside of building, and is configured to measure the temperature (that is, measuring outside air temperature) in the place being provided with outside air temperature measurement section 22.
Indoor temperature measurement portion 21 and outside air temperature measurement section 22 comprise being configured to the temperature sensor of the modulating output generating reflection environment temperature and being configured to amplify the sensor amplifier of output of this temperature sensor of such as thermistor etc. separately.Indoor temperature measurement portion 21 and outside air temperature measurement section 22 also comprise the converter section being configured to the output of sensor amplifier be converted to numerical data and the communication unit being configured to the numerical data of this converter section to be sent to room temperature estimation unit 10 separately.
Indoor temperature measurement portion 21 and outside air temperature measurement section 22 can not comprise communication unit separately or can not comprise converter section and communication unit.But consider and measured value is correctly sent to room temperature estimation unit 10, desirably, indoor temperature measurement portion 21 and outside air temperature measurement section 22 include converter section and communication unit separately.When not arranging converter section, analogue data is provided to room temperature estimation unit 10 by indoor temperature measurement portion 21 and/or outside air temperature measurement section 22.
Desirably, indoor temperature measurement portion 21 or the communication between outside air temperature measurement section 22 and room temperature estimation unit 10 are carried out as the radio communication channel of transmission medium or via wireline communication channels via utilizing radio wave.Indoor temperature measurement portion 21 can with room temperature estimation unit 10 common housing.In indoor temperature measurement portion 21 with the structure of room temperature estimation unit 10 common housing, indoor temperature measurement portion 21 need not comprise communication unit.
The outside air temperature data (measured value) that the room temperature data (measured value) room temperature obtaining portion 11 obtained and outside air temperature obtaining portion 12 obtain are stored in storage part 13 in the mode be associated with measured date and time respectively.That is, storage part 13 is configured to the group or the storage (room temperature that store (room temperature, date and time) and (outside air temperature, date and time) these two kinds of two information, outside air temperature, date and time) the group of three information.Latter instance is less in data volume, and can save the capacity of storage part 13.
The date and time be stored in storage part 13 utilizes timing unit 14 set in room temperature estimation unit 10 to carry out timing to obtain.The date and time that will obtain room temperature data and outside air temperature data is preset respectively in room temperature obtaining portion 11 and outside air temperature obtaining portion 12.Room temperature obtaining portion 11 and outside air temperature obtaining portion 12 are configured to carry out based on timing unit 14 current date and time that timing obtains and obtain room temperature data and outside air temperature data at each date and time preset respectively.In the structure shown here, expect that storage part 13 is configured to the group (room temperature, outside air temperature, date and time) of storage three information.
Such as, room temperature obtaining portion 11 and outside air temperature obtaining portion 12 are configured to separately for acquisition data per hour.Such as, room temperature obtaining portion 11 and outside air temperature obtaining portion 12 are configured to obtain data at each hour place separately.Room temperature obtaining portion 11 and outside air temperature obtaining portion 12 need not be configured to for acquisition data per hour, but can obtain data for every 10 minutes, every 15 minutes, every 30 minutes or every two hours etc. (can select as required these time intervals one of them).The time interval is shorter, and the information content obtained is larger, and this will improve the estimated accuracy of predictor formula.But this causes the data volume that will be stored in storage part 13 to increase.Therefore, preferably the time interval being used for obtaining data is set to about 1 hour time period and be arranged on 1 hour some/scope of ~ some hours in.Preferably, will room temperature obtaining portion 11 and outside air temperature obtaining portion 12 be utilized to be placed through to each time interval obtaining data the value obtained 24 hours divided by integer.
Indoor temperature measurement portion 21 and outside air temperature measurement section 22 can comprise the special timing unit being configured to measure current date and time separately.In the structure shown here, indoor temperature measurement portion 21 and outside air temperature measurement section 22 are configured to carry out based on respective self timing unit the date and time that timing obtains respectively and obtain room temperature data and outside air temperature data, and obtained data are sent to room temperature estimation unit 10.In other words, indoor temperature measurement portion 21 and outside air temperature measurement section 22 are configured to respectively respective room temperature data and outside air temperature data are sent to room temperature estimation unit 10 to carry out with self timing unit separately the mode that date and time that timing obtains is associated.
In the structure shown here, expect that storage part 13 is configured to store the group of (room temperature, date and time) and (outside air temperature, date and time) these two kinds of two information.Note, indoor temperature measurement portion 21 and outside air temperature measurement section 22 are not limited to be configured to send room temperature data or outside air temperature data when measuring room temperature or outside air temperature separately, also can be configured to the set of the data sending half a day or a day.
Be desirably in when existing poor between the date and time obtaining room temperature data and the date and time obtaining outside air temperature data, if this differs from below the half for data acquisition interval (such as, less than 1/10 of data acquisition interval), then these data be considered to be obtain in same date and time and join with this same date and time correlation.
Incidentally, when room temperature keeps not being subject to the impact at sunshine and the fluctuation of outside air temperature is little, import the heat energy in room into and will be balanced from the heat energy of room release.Therefore, in this case, the hypothesis that the outside air temperature of the synchronization of every day and room temperature illustrate linear relationship can be proposed.
The present inventor within the relatively long time period at the gentle outside air temperatures of multiple moment measuring chambers of every day.Then, by for the relation of multiple moment separately to graphically between the gentle outside air temperature in analysis room, as shown in Figure 2, the present inventor has found, at appointment moment outside air temperature and room temperature, linear relationship is shown.That is, found following content: the room temperature of specifying the moment can be represented as the predictor formula of the linear function of variable by comprising outside air temperature, and based on this predictor formula, room temperature can be estimated according to outside air temperature.Particularly, found following content: first of every day in many days specifies the outside air temperature measured by the moment and room temperature that linear relationship is shown, and second of same every day in many days specifies the outside air temperature measured by the moment and room temperature that linear relationship is shown.
In addition, in the room temperature estimation unit 10 of the present embodiment, predictor formula generating unit 15 is configured to generate predictor formula based on the outside air temperature in many days respective appointment moment and room temperature.Predictor formula generating unit 15 is configured to extract in storage part 13 appointment moment respective with many days in given extraction time section of storing corresponding room temperature data and outside air temperature data, with according to the room temperature data corresponding in the same time with many days respective phases and outside air temperature data genaration recurrence formula, and adopt this recurrence formula as predictor formula.Particularly, predictor formula generating unit 15 is configured to, based on the appointment moment (mutually in the same time) respective with many days in given extraction time section stored in storage part 13 corresponding room temperature data and outside air temperature data, generate the predictor formula of the relation between room temperature data and outside air temperature data representing and specify the moment.
Because predictor formula to be written as the linear function of outside air temperature by expection, the data of more than three days therefore should be comprised for the room temperature data of generation forecast formula and outside air temperature data.Therefore, extraction time section should be more than three days, and can be such as selected in the scope from 15 ~ 90 days.The lower limit 15 days of this scope is corresponding with 24 mid-season solar term (two weeks) in solar year, and the upper limit 90 days of this scope is corresponding with a season (that is, spring, summer, autumn or winter).The number of days of this time period is example, and can be 30 days (about one months) or also can be 1 year when the change of 1 year inside and outside temperature is little.Acquisition day for the data of generation forecast formula can comprise continuous print many days or can be discontinuous many days.Such as, predictor formula can be generated based on for the every day in 1 year ~ several years, every two days or room temperature data measured weekly and outside air temperature data.
Predictor formula generating unit 15 is configured to there is this discovery of linear relationship based between the room temperature data θ 1 (t) corresponding with the moment " t " paid close attention in extraction time section and outside air temperature data θ 2 (t), utilizes formula " θ 1 (t)=α * θ 2 (t)+β " generation forecast formula.In order to generation forecast formula, based on the known computational methods of such as least square method etc., according to room temperature data θ 1 (t) and linear function in outside air temperature data θ 2 (t) next life.That is, predictor formula generating unit 15 is configured to generate recursive prediction formula according to the room temperature data θ 1 (t) corresponding with the moment (specifying the moment) paid close attention in extraction time section and outside air temperature data θ 2 (t).
Recursive prediction formula comprise specify the outside air temperature in moment as explanatory variable and the room temperature comprising this appointment moment as dependent variable.In other words, predictor formula generating unit 15 is configured to comprise room temperature data and generate predictor formula by comprising outside air temperature data as independent variable as the simple linear recursive analysis of dependent variable.For generating moment in one day of recursive prediction formula (specifying the moment) from selected in following time-bands, wherein in this time-bands, room temperature is not by solar radiation and only depend on outside air temperature, and the change of outside air temperature relaxes relatively.Predictor formula generating unit 15 is configured to adopt the recursive prediction formula that generates as the predictor formula according to outside air temperature determination room temperature.
Predictor formula generating unit 15 is configured to generate multiple recursive prediction formula corresponding with the multiple moment in one day respectively.Predictor formula generating unit 15 is configured to generate the predictor formula of these recursive prediction formula as each moment in one day.Particularly, predictor formula generating unit 15 be configured to generate respectively with the multiple multiple predictor formulas of specifying the moment corresponding in a day.Each predictor formula generates based on the room temperature data corresponding with specifying the moment and outside air temperature data.Particularly, predictor formula generating unit 15 is configured to generate at least the first predictor formula and the second predictor formula of specifying the moment and second to specify the moment corresponding respectively with at least the first.First predictor formula generates based on the first room temperature data of specifying the moment corresponding respective with many days in extraction time section and outside air temperature data.Second predictor formula generates based on the second room temperature data of specifying the moment corresponding respective with many days in extraction time section and outside air temperature data.
Room temperature estimation unit 10 generates multiple predictor formulas corresponding with the multiple moment in one day respectively in the above described manner, then comes to estimate room temperature according to outside air temperature based on predictor formula.Particularly, room temperature estimation unit 10 generate the first predictor formula that (at least) and first specify the moment corresponding and with the second second predictor formula of specifying the moment corresponding.Room temperature estimation unit 10 adopts the first predictor formula to estimate the room temperature in the moment of specifying the moment corresponding with first, and adopts the second predictor formula to estimate the room temperature in the moment of specifying the moment corresponding with second.
Such as, room temperature estimation unit 10 based on respective at many days the morning 4 time (first specify moment) room temperature data of obtaining and outside air temperature data generate the first predictor formula, and based on respective at many days the morning 5 time (second specifies the moment) room temperature data of obtaining and outside air temperature data generate the second predictor formula.Room temperature estimation unit 10 adopt the first predictor formula to estimate certain day the morning 4 time (performing corresponding moment in moment with first) room temperature, and adopt the second predictor formula to estimate certain day the morning 5 time (moment of specifying the moment corresponding with second) room temperature.
Below describe in detail and be configured to the structure estimating room temperature according to outside air temperature in room temperature estimation unit 10.Room temperature estimation unit 10 comprises predicted time change obtaining portion 16 and room temperature estimator 17.The time series that predicted time change obtaining portion 16 is configured to the outside air temperature data (measured value) obtained from outside air temperature measurement section 22 based on outside air temperature obtaining portion 12 obtains the predicted time change of outside air temperature.Room temperature estimator 17 is configured to use the time variations of outside air temperature to estimate room temperature.
Predicted time change obtaining portion 16 is configured to any template in the template (template) of the multiple types time series of outside air temperature data being applied to the time variations of the outside air temperature of registering in advance, and predicts the time variations of outside air temperature based on applied template.Predicted time change obtaining portion 16 is configured to any template in the template of the time variations time series of outside air temperature data being applied to outside air temperature, considers the weather on the same day and/or limit the template that will apply season.
About the change of predicted outside air temperature, replace the outside air temperature data (measured value) adopting outside air temperature obtaining portion 12 to obtain from outside air temperature measurement section 22, the time variations of the outside air temperature that outside air temperature obtaining portion 12 can be adopted to obtain via the electrical communication line of such as internet etc.That is, outside air temperature obtaining portion 12 can have and is configured to via electrical communication line from the function providing the service provider of local Weather information to obtain outside air temperature data.In the structure shown here, predicted time changes the outside air temperature data that obtaining portion 16 adopts outside air temperature obtaining portion 12 to obtain from service provider.
The outside air temperature data provided via electrical communication line are data relevant with the ad-hoc location will estimated in the region that the object room of room temperature exists, instead of the outside air temperature corresponding with this object room.But the outside air temperature that it is expected to these data provided and this room has linear relationship.Therefore, room temperature estimator 17 is configured to correct room temperature estimated by outside air temperature that use provides based on the actual measured value of room temperature.As a result, suitably room temperature can be estimated based on the outside air temperature data provided via electrical communication line.
The outside air temperature of paid close attention to date and time is determined in the predicted time change of the outside air temperature that room temperature estimator 17 obtains based on predicted time change obtaining portion 16.When determining outside air temperature, room temperature estimator 17 estimates room temperature by the predictor formula determined outside air temperature being applied to predictor formula generating unit 15 and generating.In brief, room temperature estimator 17 is configured to the room temperature by carrying out following operation to estimate paid close attention to date and time: the outside air temperature of the date and time will estimating room temperature is determined in the predicted time change based on outside air temperature; And determined outside air temperature is applied to predictor formula.
Desirably, room temperature estimation unit 10 comprises notice efferent 18, and wherein this notice efferent 18 is configured to export the room temperature estimated by room temperature estimator 17 to notifying device 23.Notifying device 23 can be the device comprising display and communication function comprising the special purpose device of display or such as smart phone, panel computer and personal computer etc.When adopt these devices as notifying device 23, notice efferent 18 be configured to communicate with these devices.Notifying device 23 is as shown in phantom in Figure 1 such, and notifying device 23 can be arranged in the housing of room temperature estimation unit 10 integratedly.
Room temperature estimated by room temperature estimator 17 not only can inform user via notifying device 23, but also can be used for the device of such as ventilation fan, air-conditioning, electric-powered shutter, electrically driven curtain and the motorized window etc. controlling to affect room temperature.When control heating-cooling equipment (aircondition) heat and/or refrigerating operation, by use based on outside air temperature time variations estimated by room temperature, the suitable timing that should disconnect heating-cooling equipment can be determined.As a result, the energy that cooling and warming consumes can be saved.
Such as, in summer, when predict due to night room temperature decline thus without the need to make refrigeration plant carry out work just room temperature can be remained in comfort level, if determine the timing that will disconnect refrigeration plant, then the useless operation of refrigeration plant can be prevented with energy-conservation.Equally, in the winter time, when predict due to daytime room temperature rise thus without the need to make heating equipment carry out work room temperature just can be made to remain in comfort level, if determine the timing that will disconnect heating equipment, then the useless operation of heating equipment can be prevented with energy-conservation.
The formula of the relation that easy supposition represents between outside air temperature data and room temperature data changed according to season.Such as, in fig. 2, the data point in left side illustrates the relation between the room temperature in winter and outside air temperature, and the data point on right side illustrates the relation between the room temperature in summer and outside air temperature.Have a look at this figure, seem and can represent the data point in left group and the data point in right group by single linear function.But, as shown in Figure 3, by generating linear function respectively according to the point (utilizing in figure 3 shown in square) in left group and the point (utilizing in figure 3 shown in triangle) in right group, between these groups, obtain different predictor formulas (utilizing shown in straight line).
Therefore, the extraction time section for determining measuring room temperature that generation forecast formula uses and outside air temperature each season is expected.Therefore, in the structure shown here, the section each sliced time obtained for the segmentation of year section provides extraction time section.Desirably, sliced time the length of section corresponding with the time period (by splitting the obtained time period based on climatic environment to year section) suitably selected from 4 ~ 24 scopes split of a year (when " 1 year 4 split ", sliced time, section reflected spring, summer, autumn and winter in these four seasons; And when " 1 year 24 segmentation ", each sliced time, section was corresponding with two weeks).Can by sliced time section length be set to 15 ~ 90 days, and for each sliced time section extraction time section can be more than three days.Such as, in advance by these sliced time section and extraction time section be stored in storage part 13.
In this example, predictor formula generating unit 15 is configured to generate the corresponding multiple predictor formulas of quantity with section sliced time.Particularly, predictor formula generating unit 15 is configured to for each section generation sliced time multiple predictor formulas corresponding with the multiple moment in one day respectively.Room temperature estimator 17 is configured to select from for multiple predictor formulas that each sliced time, section generated when estimating the room temperature in certain day some time the predictor formula corresponding with the moment paid close attention to of the sliced time belonging to the paid close attention to date in section, and based on selected predictor formula, estimate room temperature according to the time variations of outside air temperature.
In another example, predictor formula generating unit 15 be configured to carry out based on timing unit 14 that date and time that timing obtains determines from one sliced time section to next sliced time section transformation (such as, transformation from time period to the time period in " winter " in " summer ") time, newly-generated multiple predictor formulas corresponding with the multiple moment in one day respectively.After generating predictor formula, room temperature estimator 17 estimates room temperature based on this newly-generated predictor formula.
embodiment 2
In embodiment 1, predictor formula generating unit 15 generates the predictor formula of measured room temperature and outside air temperature in the respective time-bands not being subject to solar radiation based on room temperature.Therefore, can estimate that the time-bands of room temperature is restricted according to outside air temperature by applied forecasting formula.In other words, accurately cannot estimate that room temperature is subject to the room temperature in the time-bands of solar radiation based on the predictor formula generated according to embodiment 1.The time-bands that the change that only can be applied to the outside air temperature of time period such as from midnight to early morning etc. according to the predictor formula of embodiment 1 relaxes relatively.
Illustrate in the present embodiment and be applicable to for determining the technology that room temperature is subject to the predictor formula of the time-bands on the daytime of solar radiation.Therefore, the time-bands at the impact for sunshine negligible night, adopts the predictor formula generated according to the technology of embodiment 1, and for considering daytime of impact at sunshine, adopts the predictor formula of the following stated.That is, in the present embodiment, by not being subject to the time-bands (that is, time-bands without sunshine) of solar radiation and room temperature, the time-bands being subject to solar radiation is adopted different types of predictor formula for room temperature.In the room temperature estimation unit 10 of the present embodiment, predictor formula generating unit 15 has the function being configured to generation two kinds of predictor formulas.
As shown in Figure 4, room temperature estimation unit 10 comprises the first predictor formula generating unit 151 and the second predictor formula generating unit 152.First predictor formula generating unit 151 is configured to generate predictor formula (the first predictor formula) based on the technology identical with the technology in embodiment 1.Second predictor formula generating unit 152 is configured to generate predictor formula (the second predictor formula) based on the technology of the following stated.
First predictor formula generating unit 151 is configured to the mode generation forecast formula identical with the predictor formula generating unit 15 in embodiment 1.First predictor formula generating unit 151 is configured to generate recursive prediction formula based on the room temperature data corresponding with many days respective appointment moment stored in storage part 13 and outside air temperature data, and the recursive prediction formula adopting this to generate is as predictor formula.
On the other hand, the second predictor formula generating unit 152 is configured to the relational dependence between room temperature and outside air temperature under thermal characteristics (such as thermal insulation and recovery electric heating system etc.) this hypothesis in room, utilizes following methods to generate predictor formula.Supposition room temperature is only depended on outside air temperature, and is undertaken transmitting and the model that changes according to the change of outside air temperature of room temperature by creating the partition wall of heat via the such as wall in room, ceiling and floor etc.In the model, the degree according to the heat conducting degree of partition wall and the accumulation of heat of partition wall changes the impact of room temperature by outside air temperature.In the present embodiment, the temperature of the air in room is considered as room temperature, and does not consider the radiant heat from partition wall.
According to above-mentioned model, room temperature will be later than the change of outside air temperature and change.The present inventor checked experimental result, and has found following situation: between the change and the change of room temperature of outside air temperature, there is special relationship; The change time delay late of outside air temperature is compared in the change of room temperature; And depend on the thermal characteristics (such as thermal insulation and recovery electric heating system etc.) of partition wall this time delay.In addition, below the present inventor has found: by determining time delay, the room temperature of specifying the moment can be represented by simple predictor formula and relative to this appointment instants offset the moment of time delay outside air temperature between relation, and can based on this predictor formula, estimate according to outside air temperature the room temperature expecting the moment.
Fig. 5 A is the figure of the point that the relation be separately between room temperature measured by same date and time and outside air temperature is shown.Have a look at this figure, seem to there is not relation between room temperature and outside air temperature.As a comparison, as mentioned above, between the time variations and the time variations of outside air temperature of room temperature, have when the present embodiment is based on the time delay being provided with the thermal characteristics depending on room that this hypothesis of correlation realizes.
Therefore, the room temperature estimation unit 10 of the present embodiment comprises evaluation section 19, wherein this evaluation section 19 be configured to based on the room temperature data stored in storage part 13 (measured value), outside air temperature data (measured value) and association date and time determine to make the coefficient correlation between room temperature and outside air temperature become maximum time delay.Evaluation section 19 is configured to based on the room temperature data in the paid close attention to specific period (hereinafter referred to as " extraction time section ") and outside air temperature data, by making the date and time of measurement room temperature data and measuring one of them relativity shift of date and time of outside air temperature data, determine to make the coefficient correlation between room temperature data and outside air temperature data become maximum time delay (hereinafter referred to as " Best Times is poor ").This, section was not limited to one day extraction time, and can be many days.In the example of the following stated, to measure the date and time of room temperature for benchmark, the date and time measuring outside air temperature offsets.But following reverse situation is also fine: to measure the date and time of outside air temperature for benchmark, the date and time measuring room temperature offsets.
In this example, " θ 1 (t) " and " θ 2 (t) " is utilized to represent the room temperature data corresponding with specific date and time " t " and outside air temperature data respectively." p " is utilized to represent the data acquisition interval of room temperature data " θ 1 (t) " or outside air temperature data " θ 2 (t) ".Formula " t=t0+n*p " is utilized to represent specific date and time " t ", and utilize formula " Δ t=m*p " to represent special time difference " Δ t ", wherein " t0 " is according to " extraction time section " determined a reference value, and " m " and " n " each natural number naturally.
According to above-mentioned labelling method, utilize " θ 1 (t0+p) ", " θ 1 (t0+2p) ", " θ 1 (t0+3p) " ... represent room temperature data, and utilize " θ 2 (t0+p) ", " θ 2 (t0+2p) ", " θ 2 (t0+3p) " ... represent outside air temperature data.Formula " θ 2 (t0+n*p-Δ t)=θ 2 (t0+ (n-m) p) " is utilized to represent that the date and time of the room temperature data compared represented by " θ 1 (t0+n*p) " has done sth. in advance the outside air temperature data of the date and time of time difference " Δ t ".
Below consider the time period being defined as the specific extraction time period of " [t0+p, t0+q*p] ".In this case, the mean value " a (θ 1) " calculating the room temperature data θ 1 (t) in the time period of this section extraction time as room temperature data θ 1 (t0+p), θ 1 (t0+2p) ..., θ 1 (t0+q*p) mean value.Calculate compare mean value " a (θ 2) " that " extraction time section " done sth. in advance the outside air temperature data θ 2 (t) in the time period of " time difference Δ t " as outside air temperature data θ 2 (t0+ (1-m) p), θ 2 (t0+ (2-m) p) ..., θ 2 (t0+ (q-m) is p) } mean value.Wherein, [t0+p, t0+q*p] represents specific closed interval, and comprise t0+p, t0+2p, t0+3p ..., q the centrifugal pump of t0+q*p}.
Evaluation section 19 be configured to based on these values calculate with specific date and time " t " corresponding room temperature data θ 1 (t) and with compared with these specific dates and time done sth. in advance between the corresponding outside air temperature data θ 2 (t-Δ t) of the date and time " t-Δ t " of time difference Δ t (=m*p) coefficient correlation.This coefficient correlation can be utilize known computational methods to calculate, and is by being obtained by the product of the covariance of data θ 1 (t) and data θ 2 (t-Δ t) divided by the standard deviation of data θ 1 (t) and the standard deviation of data θ 2 (t-Δ t).Above-mentioned mean value " a (θ 1) " and " a (θ 2) " is used to calculate this covariance and these standard deviations.Represent that the scope of the variable " t " of the date and time of room temperature data θ 1 (t) and outside air temperature data θ 2 (t-Δ t) is within the time period (that is, closed interval [t0+p, t0+q*p]) of extraction time section.
Evaluation section 19 is configured to when the value of change numerical value " m " is to change time difference Δ t, and each value for numerical value " m " calculates coefficient correlation.In the present embodiment, the maximum of logarithm value " m " limits, to make the product " m*p " in value " m " and the time interval " p " not more than the length of one day.Such as, when the time interval, " p " was corresponding with one hour, the maximum of numerical value " m " is constrained to and can not exceedes " 24 ".Evaluation section 19 is configured to the value " mm " determining the numerical value " m " corresponding with maximum correlation coefficient.Evaluation section 19 is by formula " Δ t
a=mm*p " determine Best Times difference " Δ t
a".
Fig. 5 B illustrates and is Utilization assessment portion 19 determined time difference (Best Times is poor) Δ t separately
aroom temperature data θ 1 (t) and outside air temperature data θ 2 (t-Δ t
a) between the point of relation.In this illustrated example, can find: at room temperature data θ 1 (t) and outside air temperature data θ 2 (t-Δ t
a) between there is linear relationship, and linear function can be utilized represent this relation between both.
Second predictor formula generating unit 152 is configured to generate predictor formula for estimating room temperature according to outside air temperature based on the relation shown in Fig. 5 B.Second predictor formula generating unit 152 is configured to the extraction carrying out each data in extraction time section the room temperature data that stores in storage part 13 and outside air temperature data, and by determined for evaluation section 19 time difference (Best Times is poor) Δ t
abe provided to the date and time corresponding with extracted outside air temperature data.In addition, at supposition room temperature data θ 1 (t) and outside air temperature data θ 2 (t-Δ t
a) when having linear relationship, the second predictor formula generating unit 152 is configured to utilize formula " θ 1 (t)=α * θ 2 (t-Δ t
a)+β " represent predictor formula, and utilize the known algorithmic methods of such as least square method etc. to determine coefficient " α ", " β " of this formula.Particularly, the second predictor formula generating unit 152 is provided with time difference Δ t by comprising
aoutside air temperature data comprise the simple linear recursive analysis of room temperature data as dependent variable to generate predictor formula as independent variable.Like this, evaluation section 19 determines time difference Δ t
aand the second predictor formula generating unit 152 determines coefficient " α ", " β ", result can generation forecast formula (the second predictor formula).Note, the coefficient " α " in this formula, " β " are different from coefficient " α " in the predictor formula that the first predictor formula generating unit 151 generates, " β " usually.
That is, according to the second predictor formula generating unit 152, evaluation section 19 based on the given extraction time stored in storage part 13 room temperature data in section and outside air temperature data determine the time difference (Best Times is poor), then the second predictor formula generating unit 152 is provided with the room temperature data of time difference based on one of them and outside air temperature data generate predictor formula.
The predictor formula that second predictor formula generating unit 152 generates and sunshine independently all applicable on the impact of room temperature.In addition, single predictor formula independently can be utilized to estimate room temperature with the moment in one day.But, about room temperature not by the time-bands of solar radiation, the predictor formula (the first predictor formula) that can generate based on the first predictor formula generating unit 151, with suitable precision (possibly with the precision that the precision of the predictor formula generated than the second predictor formula generating unit 152 is high), estimate room temperature according to outside air temperature.
Therefore, expect as follows: for the predictor formula that the first predictor formula generating unit 151 can be utilized to generate to estimate the time-bands of room temperature, adopt the predictor formula that the first predictor formula generating unit 151 generates, and for At All Other Times with the predictor formula that employing second predictor formula generating unit 152 generates, to share the effect of both.Particularly, (namely the time-bands of solar radiation will be subject to for room temperature, time-bands without sunshine), the predictor formula (the first predictor formula) adopting the first predictor formula generating unit 151 to generate, and the time-bands of solar radiation will be subject to for room temperature, the predictor formula (the second predictor formula) adopting the second predictor formula generating unit 152 to generate.
When the predictor formula generated based on the second predictor formula generating unit 152 to estimate room temperature according to outside air temperature, the acquisition of room temperature estimation unit 10 needs is compared paid close attention to date and time and has been done sth. in advance evaluation section 19 determined time difference (time delay) Δ t
athe outside air temperature data of date and time.Note, " date and time paid close attention to " is the date and time will estimating room temperature.
Therefore, the predicted time change of the outside air temperature that room temperature estimator 17 obtains based on predicted time change obtaining portion 16 and evaluation section 19 determined time difference (Best Times is poor), determine to compare the outside air temperature (measured value or predicted value) that paid close attention to date and time has done sth. in advance the date and time of time difference (Best Times is poor).When determining outside air temperature, room temperature estimator 17 estimates room temperature by the predictor formula determined outside air temperature being applied to predictor formula generating unit 15 and generating.In brief, room temperature estimator 17 is configured to carry out following operation: the predicted time based on outside air temperature changes to determine to compare will estimate that the date and time of room temperature has done sth. in advance the outside air temperature of the time point of evaluation section 19 determined time difference; And determined outside air temperature is applied to predictor formula, and estimates the room temperature of the date and time paid close attention to thus.
As mentioned above, the predictor formula generating unit 15 of the present embodiment comprises the first predictor formula generating unit 151 and the second predictor formula generating unit 152.Room temperature estimator 17 is configured to carry out based on timing unit 14 date and time that timing obtains, and judges that current time is subject in the time-bands of solar radiation or in room temperature by the time-bands of solar radiation in room temperature.For room temperature not by the time-bands of solar radiation, use the predictor formula that the first predictor formula generating unit 151 generates, and room temperature is subject to the time-bands of solar radiation, use the predictor formula that the second predictor formula generating unit 152 generates.
As described in Example 1, the predictor formula that the first predictor formula generating unit 151 generates will change according to season.Also easily suppose that the predictor formula that the second predictor formula generating unit 152 generates changed according to season.Therefore, the extraction time section for determining measuring room temperature that generation forecast formula uses and outside air temperature each season is expected.
Therefore, definition year section carries out splitting section sliced time obtained, and provides extraction time section for section each sliced time.Sliced time section length be suitably select from the scopes of 4 ~ 24 in 1 year segmentations (when " 4 segmentations of a year ", sliced time section reflection spring, summer, autumn and winter in these four seasons; And when " 1 year 24 segmentation ", each sliced time, section was corresponding with two weeks).
In the structure shown here, the second predictor formula generating unit 152 generates the corresponding predictor formula of quantity of number and section sliced time.Room temperature estimator 17 selects the predictor formula corresponding with section sliced time belonging to paid close attention to date and time from for the determined multiple predictor formula of each section sliced time, and predictor formula selected by use, estimates room temperature according to the time variations of outside air temperature.
It should be noted that the thermal characteristics in room likely changes because of aging.Therefore, desirably, room temperature estimator 17 is configured to, when estimating room temperature, adopt for each sliced time section determined time difference.Particularly, expect as follows: evaluation section 19 at every turn through sliced time section stylishly determine time difference (Best Times is poor) Δ t
a, the newly-generated time difference Δ t with newly determining of the second predictor formula generating unit 152
acorresponding predictor formula (the second predictor formula), and room temperature estimator 17 estimates room temperature based on newly-generated predictor formula (the second predictor formula).But room temperature estimator 17 can be configured to estimate room temperature based on for any sliced time section determined time difference.Room temperature can also be estimated based on the mean value for multiple sliced time section determined time difference.
As mentioned above, whether the room temperature estimator 17 in the present embodiment is subject to solar radiation according to room temperature and uses different types of predictor formula.In addition, the outside air temperature applied is different according to the kind of predictor formula.Therefore, the precision of prediction of room temperature can be improved.Other structure with operation with the structure in embodiment 1 with operate identical.
embodiment 3
In embodiment 1 and embodiment 2, room temperature estimation unit 10 is configured to only estimate room temperature based on outside air temperature.But as mentioned above, when not carrying out cooling and warming, the factor that room temperature relies on comprises the number in sunshine, ventilation, rainfall and room.Note, if utilize the heating-cooling equipment with the function controlling room temperature to carry out cooling and warming, then the temperature-independent in room, in the mode of operation of heating-cooling equipment, does not therefore predict room temperature by predictor formula.Therefore, in the following description, assuming that do not carry out cooling and warming.
In order to also consider the information of sunshine, ventilation, rainfall and existing number except outside air temperature, create considering the model being used for each information and room temperature are linked together, and by with each information-related numerical applications in this model.But because the causality between these factors is complicated, therefore this model needs complicated computer simulation.As a result, this model needs input quantity of parameters and produces great processing load.
Therefore, in order to the increase of the increase and processing load that prevent number of parameters, each information is considered as control information by the present embodiment, limits the quantity of the possible state of various control information, and for each state determination predictor formula of control information.When there is multiple control information, the state of control information is divided into multiple grade for various control information by predictor formula generating unit 15.Then, predictor formula generating unit 15 generates predictor formula (correction predictor formula) corresponding with the particular combination of the grade of multiple control information separately.To illustrate that the technical scheme of the present embodiment is applied to the example of the structure of the embodiment 1 shown in Fig. 1, but the technical scheme of the present embodiment can also be applied to the structure of embodiment 2.
In the present embodiment, for each self-defined two grades (having and nothing) of sunshine, ventilation and rainfall.On the contrary, about there is number, assuming that for everyone, the temperature value (such as, 0.5 DEG C) making room temperature rise predetermined.By simplifying the kind of control information and limiting the quantity of the possible state of various control information, the quantity of the combination of each control information is limited and relatively little.
Predictor formula generating unit 15 is configured to arrange predictor formula according to the combination of each state of multiple control information.Number in room is only reflected on the coefficient " β " of predictor formula.Therefore, different predictor formulas need not be generated according to number.About the correction according to number, room temperature estimator 17 can be configured to the product of existing number and predetermined temperature to be added with the room temperature estimated by predictor formula.Therefore, in the examples described above, according to the control information of these kinds relevant with sunshine, ventilation and rainfall, 8 predictor formulas are generated.
Predictor formula generating unit 15 is configured to the coefficient " α " and " β " that correct predictor formula according to the state of each control information, and generates correction predictor formula thus.Such as, coefficient " α " and the correcting value of " β " is made to be associated with the state of each control information and to be stored in storage part 13.When a kind of control information is in particular state (such as, when there is ventilation), predictor formula generating unit 15 reads the correcting value of the coefficient " α " corresponding with this particular state and " β " from storage part 13, and read-out correcting value is applied to the coefficient " α " of predictor formula and " β " and generation correction predictor formula thus.
As shown in Figure 6, the temperature estimation rneans 10 of the present embodiment comprises control information obtaining portion 32, wherein this control information obtaining portion 32 be configured to from sunshine test section 33, ventilation test section 34, rainfall test section 35 and number test section 36 obtain each control information.
Test section 33 can comprise the photoelectric detector of such as photodiode and phototransistor etc. and be configured to the output of photoelectric detector and threshold value to compare to judge the judging part of light quantity sunshine.The impact of sunshine on room depends on curtain and/or roller shutter is opened or closed.Therefore, expect that sunshine, test section 33 had the function being configured to detect curtain and/or roller shutter and opening or close.
Whether ventilation test section 34 can be configured to detect ventilation fan and to work and/or detection window is opened or closes and/or measures the air-flow in room.Rainfall test section 35 can be configured to for each special time period collect rainwater with measure collected rainwater weight and/or outdoor image detect with or without raindrop.The information that can provide via the electrical communication line of such as internet etc. according to service provider obtains the control information relevant with rainfall.Number test section 36 can be configured to the number come based on off-the-air picture in measuring chamber.
Replacement only " has " and these two grades of "None", the state of the control information relevant with sunshine, ventilation and rainfall can be divided into the grade of more than three according to degree.Can by the state demarcation precedent at sunshine as " by force ", " in ", " weak " and " faint " these four grades.Equally, ventilation and/or the state demarcation of rainfall can be become the grade of more than three.
Room temperature estimator 17 corrects predictor formula based on the control information that control information obtaining portion 32 obtains and corrects predictor formula to generate, and based on this correction predictor formula, estimate room temperature according to outside air temperature.Note, can statistically determine the coefficient " α " corresponding with each grade of sunshine, ventilation, rainfall and number and the correcting value of " β " based on actual measured value.Other structure with operation with the structure in embodiment 1 or embodiment 2 with operate identical.
Claims (9)
1. a room temperature estimation unit, comprising:
Room temperature obtaining portion, it is configured to obtain room temperature data;
Outside air temperature obtaining portion, it is configured to obtain outside air temperature data;
Storage part, it is configured to the outside air temperature data that the room temperature data that described room temperature obtaining portion obtained and described outside air temperature obtaining portion obtain and stores in the mode be associated with measured date and time respectively;
Predictor formula generating unit, it is configured to, based on the appointment moment respective with many days in predetermined extraction time section stored in described storage part corresponding room temperature data and outside air temperature data, generate the predictor formula of the relation between room temperature data and outside air temperature data representing the described appointment moment;
Predicted time change obtaining portion, it is configured to the predicted time change obtaining outside air temperature; And
Room temperature estimator, it is configured to the time variations of the outside air temperature obtained based on described predicted time change obtaining portion, be applied to described predictor formula by with the outside air temperature in described concern moment of specifying the moment corresponding, estimate the room temperature in described concern moment thus.
2. room temperature estimation unit according to claim 1, wherein,
Described predictor formula generating unit be configured to generate specify the moment and second to specify the moment corresponding respectively with at least the first at least the first predictor formula and the second predictor formula as described predictor formula, wherein said first predictor formula generates based on the described first room temperature data of specifying the moment corresponding respective with many days in described extraction time section and outside air temperature data, and described second predictor formula generates based on the described second room temperature data of specifying the moment corresponding respective with many days in described extraction time section and outside air temperature data, and
Described room temperature estimator is configured to carry out following operation:
Be applied to described first predictor formula by with the described first first outside air temperature paying close attention to the moment of specifying the moment corresponding, estimate the room temperature in described first concern moment thus, and
Be applied to described second predictor formula by with the described second second outside air temperature paying close attention to the moment of specifying the moment corresponding, estimate the room temperature in described second concern moment thus.
3. room temperature estimation unit according to claim 1 and 2, wherein, described predictor formula generating unit is configured to generate recurrence formula as described predictor formula according to room temperature data and outside air temperature data.
4. room temperature estimation unit according to any one of claim 1 to 3, wherein,
Described extraction time, section was for determined within 1 year, carrying out multi-split obtained each sliced time section based on climatic environment, and
Described room temperature estimator is configured to based on for the room temperature data in predetermined section sliced time section of determined described extraction time and outside air temperature data and the predictor formula generated is applied to the prediction of the room temperature in this of section predetermined sliced time.
5. room temperature estimation unit according to any one of claim 1 to 4, wherein, also comprise control information obtaining portion, described control information obtaining portion be configured to obtain beyond outside air temperature affect room temperature with from the corresponding control information of a state selected in multiple state
Wherein, the state that described predictor formula generating unit is configured to the control information obtained according to described control information obtaining portion corrects described predictor formula, generates thus and corrects predictor formula, and
Described room temperature estimator is configured to estimate room temperature based on described correction predictor formula.
6. room temperature estimation unit according to any one of claim 1 to 5, wherein, also comprises notice efferent, and described notice efferent is configured to export room temperature estimated for described room temperature estimator to notifying device.
7. room temperature estimation unit according to any one of claim 1 to 6, wherein, described outside air temperature obtaining portion is configured to obtain the outside air temperature data provided via electrical communication line.
8. room temperature estimation unit according to claim 3, wherein, described predictor formula generating unit is configured to comprise room temperature data and generate described predictor formula by comprising outside air temperature data as independent variable as the simple linear recursive analysis of dependent variable.
9. a program, it is configured to make computer be used as room temperature estimation unit according to any one of claim 1 to 8.
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| PCT/JP2014/000056 WO2014109290A1 (en) | 2013-01-11 | 2014-01-09 | Room temperature estimating device, program |
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| JP6845784B2 (en) * | 2017-11-08 | 2021-03-24 | 株式会社東芝 | Information processing equipment, information processing methods and programs |
| JP6958314B2 (en) * | 2017-12-13 | 2021-11-02 | 株式会社デンソーウェーブ | Whole building air conditioning system |
| JP7079955B2 (en) * | 2017-12-29 | 2022-06-03 | ナガノサイエンス株式会社 | Temperature characterization method |
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| 孙靖等: "基于季节性时间序列模型的空调负荷预测", 《电工技术学报》 * |
| 徐今强等: "空调负荷预测模型及仿真研究", 《华中科技大学学报（自然科学版）》 * |
| 胡昶等: "基于温度检测和神经网络的空调负荷预测", 《仪器仪表学报》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| JP6160945B2 (en) | 2017-07-12 |
| EP2944891B1 (en) | 2019-09-11 |
| EP2944891A1 (en) | 2015-11-18 |
| CN104919252B (en) | 2017-10-24 |
| WO2014109290A1 (en) | 2014-07-17 |
| EP2944891A4 (en) | 2016-04-20 |
| JP2014134360A (en) | 2014-07-24 |
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